The Evolving Landscape of Gastrointestinal Oncology: Integrating Artificial Intelligence, Molecular Profiling, and Clinical Translation

  • 944

    Total views and downloads

About this Research Topic

Submission deadlines

  1. Manuscript Submission Deadline 17 March 2026

  2. This Research Topic is currently accepting articles.

Background

Gastrointestinal (GI) cancers—including colorectal, gastric, pancreatic, hepatic, and esophageal malignancies—remain among the most lethal and complex diseases worldwide. Despite advancements in surgical techniques, systemic therapies, and diagnostic modalities, outcomes for many patients remain suboptimal due to late diagnosis, tumor heterogeneity, and resistance to therapy. Recent breakthroughs in molecular oncology and the advent of artificial intelligence (AI) are transforming our understanding of GI cancer pathogenesis and enabling a new era of precision oncology.



This Research Topic aims to highlight cutting-edge developments at the intersection of artificial intelligence, molecular profiling, and translational research in GI malignancies. We invite original research, reviews, and perspective articles that explore how AI-driven approaches—such as machine learning, deep learning, and radiomics—are being leveraged to decode the molecular landscape of GI cancers, from genomic and transcriptomic alterations to immune microenvironment characterization. Special emphasis will be placed on studies that translate these discoveries into meaningful clinical applications, including early detection, prognostication, treatment stratification, and real-time decision support.



We also welcome contributions exploring:

- Integration of multi-omics data (genomics, epigenomics, proteomics, metabolomics) using AI algorithms

- AI-assisted pathology, radiology, and endoscopy in GI cancer diagnostics

- Novel biomarker discovery and therapeutic target identification

- Computational modeling of tumor behavior, treatment response, and disease progression

- Clinical trials and real-world evidence evaluating AI-based tools in GI oncology



By bringing together interdisciplinary expertise—from oncology, bioinformatics, pathology, computational biology, and clinical gastroenterology—this collection seeks to foster a comprehensive dialogue on how intelligent technologies and molecular insights can be synergistically applied to transform the GI cancer care continuum.



We encourage submissions from both academic researchers and clinician-scientists, particularly those working on translational pipelines that connect bench discoveries to bedside applications. Through this Research Topic, we hope to provide a platform that accelerates innovation, encourages global collaboration, and ultimately improves outcomes for patients affected by GI cancers.

Article types and fees

This Research Topic accepts the following article types, unless otherwise specified in the Research Topic description:

  • Brief Research Report
  • Case Report
  • Clinical Trial
  • Editorial
  • FAIR² Data
  • FAIR² DATA Direct Submission
  • General Commentary
  • Hypothesis and Theory
  • Methods

Articles that are accepted for publication by our external editors following rigorous peer review incur a publishing fee charged to Authors, institutions, or funders.

Keywords: Multi-omics Integration, AI-assisted Diagnostics, Tumor Heterogeneity, Biomarker Discovery, Treatment Stratification

Important note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.

Topic editors

Topic coordinators

Manuscripts can be submitted to this Research Topic via the main journal or any other participating journal.

Impact

  • 944Topic views
  • 415Article views
View impact